A Web3 First: China Leverages Cross-Border AI Data For Industrial Use
In a world-first, China's Shenzhen Data Exchange (SDEx) facilitates a deal that brings decentralized, community-sourced AI data into real industrial applications through Web3 infrastructure. SDEx is the largest provider of national-level data trading platforms for data marketization and cross-border circulation in China's digital economy. The platform provides a comprehensive suite of services, including compliance protection, circulation support, supply and demand connection, and ecological development, enabling businesses and consumers to trade data efficiently.
In my previous articles, I emphasized that data will inevitably become the next key battleground frontier in AI's global race. This article delves into how SDEx has taken a significant leap forward in cross-border data collection through a commercially viable model powered by Decentralized AI (DeAI).
First, let's reiterate the looming bottleneck facing the global AI industry: data scarcity. As industries and companies increasingly rely on AI models for innovation, the demand for high-quality training data will skyrocket. This challenge cuts across sectors:
The fundamental question then becomes: where can we source this immense volume of data at scale? Traditional centralized data collection methods encounter significant limitations:
While the chipset race dominates headlines, a quieter but equally crucial data war is underway. Recently, the SDEx facilitated a commercial deal between Shenzhen Intellifusion Technologies, a publicly listed Chinese AI company, and OORT, a decentralized AI solution provider.
Intellifusion has been developing industry-specific AI solutions to enhance its smart factory capabilities. Specifically, they needed industrial datasets, including images of professional respiratory masks and confined-space ventilation ducts, among other things. OORT enabled the collection of this data through its product solution, OORT DataHub. It achieved this by distributing data collection tasks to its global community, spanning over 130 countries. Participants could contribute their data and earn crypto incentives, a feat unattainable through traditional banking or Web2 platforms. This deal marks the realization of the first commercially viable model for truly decentralized, global data collection, a significant advancement in cross-border data services.
While established platforms like Amazon's AWS Data Exchange (ADX) exist, they possess limitations that hinder the next phase of AI's global advancement:
Reflecting this context, the DeAI space has recently made remarkable strides toward building a more open AI future amidst growing concerns over the centralized model's dominance by a few major players. Notably, two DeAI alliances emerged on the same day.
First, HumanAIx, founded by 13 Web3 entities, including OORT, YGG, NEO, and io.net, introduced an open protocol designed to connect partners seamlessly. Each participant contributes essential components—validation, storage, computing, and data—to establish a permissionless, scalable, and verifiable decentralized AI infrastructure. Its three-layer architecture—interface, protocol (integrating compute, storage, and data), and security—leverages industry expertise to foster an open environment for the future of DeAI.
Simultaneously, another coalition of Web3 leaders, including NEAR, Aethir, and Coinbase, formed the Open Agents Alliance (OAA), which aims to ensure secure, open-source, economical, and fair AI access.
Despite crypto's recent bearish turn and the AI sector's vulnerability to hype and inflated narratives, it's promising to see serious industry players working on potentially profound and sustainable solutions. Only projects with viable business models will endure. SDEx has taken a significant step by embracing decentralized data collection, a move that signals a broader shift with global implications. This development suggests an important shift is underway, prompting industry participants to reconsider how they gather, verify, and manage data for AI development.
Disclosure: I am the founder and CEO of OORT.
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